Dissimilarity-based classification of chromatographic profiles

This paper proposes a non-parametric method for the classification of thin-layer chromatographic (TLC) images from patterns represented in a dissimilarity space. Each pattern corresponds to a mixture of Gaussian approximation of the intensity profile. The methodology comprises various phases, including image processing and analysis steps to extract the chromatographic profiles and a classification phase to discriminate among two groups, one corresponding to normal cases and the other to three pathological classes. We present an extensive study of several dissimilarity-based approaches analysing the influence of the dissimilarity measure and the prototype selection method on the classification performance. The main conclusions of this paper are that, Match and Profile-difference dissimilarity measures present better results, and a new prototype selection methodology achieves a performance similar or even better than conventional methods. Furthermore, we also concluded that simplest classifiers, such as k-NN and linear discriminant classifiers (LDCs), present good performance being the overall classification error less than 10% for the four-class problem.     

Stepwise dissection and visualization of the catalytic mechanism of haloalkane dehalogenase LinB using molecular dynamics simulations and computer graphics

The different steps of the dehalogenation reaction carried out by LinB on three different substrates have been characterized using a combination of quantum mechanical calculations and molecular dynamics simulations. This has allowed us to obtain information in atomic detail about each step of the reaction mechanism, that is, substrate entrance and achievement of the near-attack conformation, transition state stabilization within the active site, halide stabilization, water molecule activation and subsequent hydrolytic attack on the ester intermediate with formation of alcohol, and finally product release. Importantly, no bias or external forces were applied during the whole procedure so that both intermediates and products were completely free to sample configuration space in order to adapt to the plasticity of the active site and/or search for an exit. Differences in substrate reactivity were found to be correlated with the ease of adopting the near-attack conformation and two different exit pathways were found for product release that do not interfere with substrate entrance. Additional support for the different entry and exit pathways was independently obtained from an examination of the enzyme's normal modes.     

Guidelines for the incremental identification of aspects in requirements specifications

The desired principle of separation of concerns in software development can be jeopardized by the so-called crosscutting concerns, which tend to be scattered over (and tangled with) the functionality of the modular units of a system. The correct identification of such concerns (and their encapsulation into separate artifacts) is thereby considered a way to improve software understanding and evolution. Pursuing a proper management of concerns from the requirements engineering stage can greatly benefit the entire software life-cycle. In this paper, we propose conceptual guidelines on how to perform the identification of crosscutting concerns in the process of building requirements specifications. We argue that the identification must be carried out in an incremental way, to encapsulate apart the crosscutting concerns even if they have not emerged completely yet.

Quantum statistical foundation to the fermi liquid model and Ginzburg-Landau wave function

An energy eigenvalue equation for a quasi-particle is derived, starting with the Heisenberg equation of motion for an annihilation operator. An elementary derivation of the Fermi liquid model having a sharply defined Fermi surface in thek-space is given, starting with a realistic model of a metal including the Coulomb interaction amongand between electrons and lattice-ions. The Ginzburg-Landau wave function (r), where represents the superconducting pairon (Cooper-pair) state, is shown to be connected with the one-pairon density operatorn by (r) = r¦_n ^1/2¦. A close analogy between supercurrent and laser is indicated.On sabbatical leave from Department of Physics and Astronomy, State University of New York at Buffalo, Buffalo, New York.     

Computing the homology of groups: The geometric way

In this paper, we present several algorithms related with the computation of the homology of groups, from a geometric perspective (that is to say, carrying out the calculations by means of simplicial sets and using techniques of Algebraic Topology). More concretely, we have developed some algorithms which, making use of the effective homology   method, construct the homology groups of Eilenberg–MacLane spaces K(G,1)$K(G,1)$ for different groups G$G$, allowing one in particular to determine the homology groups of G$G$.     

An open-source library for the numerical modeling of mass-transfer in solid oxide fuel cells

The generation of direct current electricity using solid oxide fuel cells (SOFCs) involves several interplaying transport phenomena. Their simulation is crucial for the design and optimization of reliable and competitive equipment, and for the eventual market deployment of this technology. An open-source library for the computational modeling of mass-transport phenomena in SOFCs is presented in this article. It includes several multicomponent mass-transport models (i.e. Fickian, Stefan–Maxwell and Dusty Gas Model), which can be applied both within porous media and in porosity-free domains, and several diffusivity models for gases. The library has been developed for its use with OpenFOAM^®, a widespread open-source code for fluid and continuum mechanics. The library can be used to model any fluid flow configuration involving multicomponent transport phenomena and it is validated in this paper against the analytical solution of one-dimensional test cases. In addition, it is applied for the simulation of a real SOFC and further validated using experimental data.Program summaryProgram title: multiSpeciesTransportModelsCatalogue identifier: AEKB_v1_0Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEKB_v1_0.htmlProgram obtainable from: CPC Program Library, Queen?s University, Belfast, N. IrelandLicensing provisions: GNU General Public LicenseNo. of lines in distributed program, including test data, etc.: 18 140No. of bytes in distributed program, including test data, etc.: 64 285Distribution format: tar.gzProgramming language:: C++Computer: Any x86 (the instructions reported in the paper consider only the 64 bit case for the sake of simplicity)Operating system: Generic Linux (the instructions reported in the paper consider only the open-source Ubuntu distribution for the sake of simplicity)Classification: 12External routines: OpenFOAM® (version 1.6-ext) (http://www.extend-project.de)Nature of problem: This software provides a library of models for the simulation of the steady state mass and momentum transport in a multi-species gas mixture, possibly in a porous medium. The software is particularly designed to be used as the mass-transport library for the modeling of solid oxide fuel cells (SOFC). When supplemented with other sub-models, such as thermal and charge-transport ones, it allows the prediction of the cell polarization curve and hence the cell performance.Solution method: Standard finite volume method (FVM) is used for solving all the conservation equations. The pressure-velocity coupling is solved using the SIMPLE algorithm (possibly adding a porous drag term if required). The mass transport can be calculated using different alternative models, namely Fick, Maxwell–Stefan or dusty gas model. The code adopts a segregated method to solve the resulting linear system of equations. The different regions of the SOFC, namely gas channels, electrodes and electrolyte, are solved independently, and coupled through boundary conditions.Restrictions: When extremely large species fluxes are considered, current implementation of the Neumann and Robin boundary conditions do not avoid negative values of molar and/or mass fractions, which finally end up with numerical instability. However this never happened in the documented runs. Eventually these boundary conditions could be reformulated to become more robust.Running time: From seconds to hours depending on the mesh size and number of species. For example, on a 64 bit machine with Intel Core Duo T8300 and 3 GBytes of RAM, the provided test run requires less than 1 second.     

SNR gap approximation for M-PSK-Based bit loading

Adaptive OFDM has the potential of providing bandwidth-efficient communications in hostile propagation environments. Currently, bit loading algorithms use M-ary quadrature amplitude modulation of the OFDM sub-carriers, where the number of bits per symbol modulating each of them is obtained in order to maximize the performance. SNR gap approximation for M-QAM signaling makes the algorithms simpler to implement. However, in some circumstances it may be preferable to use. M-ary phase shift keying. In this letter an approximation is derived for M-PSK similar to the SNR gap of M-QAM so that bit loading algorithms can be extended to this type of modulation. In addition, the performance obtained when using M-PSK is compared to that of M-QAM in a practical situation.     

Pollution Buildup on Road Surfaces

Samples of sediment found on an urban road in Aberdeen (Scotland) were collected by washing designated surfaces. This method, called the “wet” method, was capable of collecting sediment of the smallest particle size range that is normally left behind by traditional sampling techniques using dry vacuuming. Over 17 months (mainly on a weekly basis), 66 samples were collected and analyzed for sediment loading, particle size distribution, concentration of heavy metals (Zn, Cu, Pb, Cd) in four sediment size fractions, and several dissolved pollutants in the effluent collected from washing (NO3?,?SO42?,?PO43?,?Cl?,?F?,?NH4+, total organic carbon, total carbon). Standard statistical methods, including multiple regressions, were used to determine relationships amongst different sediment characteristics. It was found that sediment loading, as well as concentrations of Cl? and SO42?, were highest in the winter months, especially when snow was present on the road surface. It was observed that 66% of total road sediment loading was found within a 0.5 m strip next to the curb. The average sediment particle sizes found were smaller than those previously recorded in the literature. As expected, the concentrations of heavy metals were highest in the smallest particle size fraction analyzed (<63?μm), and this occurred during the summer months when less sediment was available on the street surface. The antecedent dry weather period had a very weak and negative influence on the loading rate of the smallest particle size fraction next to the curb.     

Influence diagnostics in regression with complex designs through conditional bias

One of the areas of Statistics in which the influence analysis has been widely studied is the multiple linear regression model. Nevertheless, the influence diagnostics proposed in this context cannot be applied to regression in complex survey, under randomized inference, since the i.i.d. case does not incorporate any probability weighting or population structure, such as clustering, stratification or measures of size into the analysis. In this paper we introduce some influence diagnostics in regression in complex survey. They are built on the conditional bias concept (Moreno-Rebollo et al., 1999). We emphasize the similarities and differences of the proposed measures with respect to the existing ones for the i.i.d. case. Research partly supported by the Spanish MCYT grant BFM2001-3844 and Spanish MEC grant MTM2004-0111433.